CASToR - Customizable and Advanced Software for Tomographic Reconstruction

CASToR is an open-source multi-platform project for 4D emission (PET and SPECT) and transmission (CT) tomographic reconstruction. This platform is a scalable software providing both basic image reconstruction features for "standard" users and advanced tools for specialists in the reconstruction field, to develop, incorporate and assess their own methods in image reconstruction (such as specific projectors, optimization algorithms, dynamic data modeling, kinetic models, etc) through the implementation of new classes.


A generic and flexible input data file format has been designed in order to integrate all the information needed for the reconstruction, for any modality and for any data format (list-mode or histogram). Being strictly a reconstruction software, and due to its generic design, CASToR will not estimate correction factors specific to each data channel (namely normalization, attenuation, scattered and random counts, etc.), so all these corrections should be pre-computed and embedded in the data file.


Our aim is to design a generic core algorithm flexible enough to cope with the particularities of each imaging modality through a user-friendly class system allowing for the integration of new methods.


CASToR is highly portable on different platforms and it does not depend on any library for a standard use (i.e. on a single multi-core computer). The compilation of the source code is fast, straightforward and does not require being a computer geek. Binaries compiled for Unix and Windows 64-bits systems and Windows 32-bits systems are also provided.


The current version is 3.1.1

 


To download the CASToR package, please first fill-in the registration form.


  • A complete list of features included in the current version of CASToR can be found in the features section.
  • Comprehensive information about how to use CASToR as well as about CASToR classes, architecture, plug-in system and data file formats can be found in the documentation section.
  • Benchmarks, scripts and datasets to test the CASToR platform can be downloaded from the benchmarks section.
  • Data file converters for real scanners can be found in the data converters section. This page will be updated as converters for other systems become available. It also contains information regarding the conversion of data-sets from some simulation platforms.
  • Image viewer softwares which can be used to read CASToR output images are listed in the links section, as well as several Monte-Carlo simulation platforms containing tools to convert simulated data to CASToR datafiles, and alternative reconstruction softwares/programs.
  • If you encounter any difficulties using CASToR, please send an e-mail describing the issue to the mailing-list.

 

 

Please cite the following reference if you used CASToR in your work:

  • Thibaut Merlin, Simon Stute, Didier Benoit, Julien Bert, Thomas Carlier, Claude Comtat, Marina Filipovic, Frédéric Lamare, and Dimitris Visvikis,
    CASToR: a generic data organization and processing code framework for multi-modal and multi-dimensional tomographic reconstruction, PDF

    Physics in Medicine & Biology, 63 (18)5505, 2018.